Didactics

Through didactics fellows will learn fundamentals of health information technology administration and management, with particular focus on the role that informatics serves the organization beyond computerized medical records or provide order entry. Particular emphasis will be on the impact of clinical systems on processes of care and the impact that transitions to electronic health records has have had on clinicians satisfaction and patients outcomes.

Combined Harvard ACGME Clinical Informatics Lectures Series

Fellows participate in the Combined Harvard ACGME Clinical Informatics weekly lecture series and monthly Grand Rounds which is a series co-sponsored by the 3 Harvard Clinical Informatics fellowship programs and the Harvard Department of Biomedical Informatics.

IN 601.0 Medicine and Management

This joint course between Harvard Medical School and Harvard Business School provides an overview of the structure and function of health care institutions and illustrates the role of these organizations in producing successful clinical outcomes. Class sessions, assigned readings, and written assignments offer a multidisciplinary perspective combining component academic disciplines of management and medicine. Syllabus

BMI 720.0 Introduction to Clinical Informatics

This core course in the Harvard Master's program in Biomedical Informatics provides a detailed overview of clinical informatics for professionals who will work at the interface of clinical care, information technology, and the healthcare system. Students will learn how to analyze, design, implement, and evaluate information and communication technologies found in hospitals, physician offices, and other healthcare settings including the home. Emphasis will be placed on the evolution of the electronic health record and its use to promote patient care that is safe, efficient, effective, timely, patient-centered and equitable. Students will also study implementation failures and unintended consequences of systems. The course will cover the fundamental concepts in clinical informatics such as evidence-based care and clinical workflow analysis. Students will not only study health information systems but have assignments to evaluate some real-life systems at local hospitals. Through case-based analysis, students analyze the life-cycle management of complex clinical computing systems. This course is geared towards physicians seeking postgraduate training. Syllabus

Informatics Journal Club

Follow the Order Series

In the Follow the Order series, fellows follow how an order is generated at the point of care and how it is processed and fulfilled downstream. In this series, fellows also learn how EHR's are used in various clinical departments, how they function, and how clinical care processes are supported. The following is an example of some of the sessions in the series:

Ambulatory EHR

Inpatient EHR

Emergency Department Dashboard

Critical Care

Perioperative and Anesthesia

Radiology / RIS

Clinical Pathology / Laboratory / LIS

Pharmacy

Admit / Discharge / Transfer system (ADT)

Billing and Coding

Data Center

3D Printing / Maker Lab

Asynchronous Learning

Core concepts in Clinical Informatics will be delivered via professionally created video lectures by our faculty through our Online Learning Portal (only available within intranet). These core concepts in Clinical Informatics will be reinforced with small group sessions moderated by faculty. Example video lectures include:

The Field of Clinical Informatics:Introduction to informatics, and core content of the curriculum.

A History of Computing at BIDMC:Lessons from 45 years of clinical computing

Back to the Future: LINC with Tomorrow: 1967 video with Dr. Warner Slack for forerunner of PBS Nova

Patient Portals: Patient portals are tools patients can use to access their data.

Big Data - The Four V's: Introduction to the meaning of "big data" and the four "V"s

Usability of Electronic Health Records Module: Usability Assessment

Intro to Natural Language Processing (NLP): NLP is a technology for a computer to parse human language and extract concepts.

Self-Directed Learning

As part of a trainee's individualized learning plan, fellows will undertake self-directed learning depending on their interests and abilities. Some fellows will undertake additional coursework in research methdology, machine learning, computer programming, management, and other topics. This can be fulfilled through online coursework as well as traditional courses through any of the Harvard Graduate Schools (medical, business, public health, etc.) as well as at MIT.